Raster Map Analysis

 

Multiscale Advanced Raster Map Analysis for Sustainable Environment
and Development

Consider a 21st Century digital government scenario of the following nature:  What message does a remote sensing-derived land cover land use map have about the large landscape it represents? And at what scale and at what level of detail?...Does the spatial pattern of the map reveal any societal, ecological, environmental condition of the landscape? And therefore can it be an indicator of change?...How do you automate the assessment of the spatial structure and behavior of change to discover critical areas, hot spots, and their corridors?...Is the map accurate? How accurate is it? How do you assess the accuracy of the map? Of the change map over time for change detection? What are the implications of the kind and amount of change and accuracy on what matters, whether climate change, carbon emission, water resources, urban sprawl, biodiversity, indicator species, or early warning? And with what confidence, even with a single map/change-map? ...The needed research is expected to find answers to these questions and a few more that involve multicategorical raster maps based on remote sensing and other geospatial data.  It is also expected to design a prototype advanced raster map analysis system for digital governance.

0) Perspectives

0.1   Patil, G. P. (2000).  Multiscale advanced raster map analysis for sustainable environment and development: A Research and Outreach Prospectus of Advanced Mathematical, Statistical and Computational Approaches Using Remote Sensing Data. DEVELOPMENT AND IMPLEMENTATION OF A PROTOTYPE MARMAP Remote Sensing Application, Technology and Education for Multiscale Advanced Raster Map Analysis Program.

0.2  Patil, G. P.  (2001).  Multiscale advanced raster map information science and technology: A research and outreach prospectus of advanced mathematical, statistical, and computational approaches using remote sensing data:  Development and implementation of a user friendly MARMAP System

0.3  Patil, G. P. (2001).  Linkage of multiscale multisource multi-tier data for the purposes of regional assessments and monitoring: A research and outreach prospectus of advanced mathematical, statistical, and computational approaches.

0.4  Patil, G. P. (2001).  Cost effective ecological synthesis and environmental analysis research and outreach: A prospectus.

0.5  Patil, G. P. (2001).  Biocomplexity of Ecosystem Health and Its Measurement at the Landscape Scale.  A Research and Outreach Prospectus of Advanced Mathematical, Statistical and Computational Approaches Using Remote Sensing Data and GIS. DEVELOPMENT AND IMPLEMENTATION OF A PROTOTYPE MARMAP Remote Sensing Application, Technology and Education for Multiscale Advanced Raster Map Analysis Program for Biocomplexity of Ecosystem Health and Its Measurement at the Landscape Scale.

0.6  Patil, G. P. (2001).  Characterization, Evaluation, and Validation of Ecosystem Health and Its Measurement at the Landscape Scale.  A Research and Outreach Prospectus of Advanced Mathematical, Statistical and Computational Approaches Using Remote Sensing Data. A Research and Outreach Prospectus of National and International Case Studies for Evaluation, Refinement, and Validation.

0.7  Patil, G. P. (2001).  Classification and Prioritization of Watersheds for Monitoring, Protection, and Restoration.  A Research and Outreach Prospectus of Advanced Mathematical, Statistical and Computational Approaches Using Pertinent Geospatial Information and Remote Sensing. Characterization, Evaluation, and Validation of Watershed Characterization Model and Watershed Prioritization Model.

0.8  Patil, G. P. (2002).  Multiscale Advanced Raster Map Analysis System: Geographical Surveillance for Hotspot Detection, Delineation, and Prioritization: Spatial Scan Statistics for Irregularly Shaped Clusters and Early Warning System.  A Research and Outreach Prospectus.

0.9  Patil, G. P. (2002).  Multiscale Advanced Raster Mapy Analysis System: Geographical Surveillance for Hotspot Detection, Delineariton, and Prioritization: Spatial Scan Statistics for Irregularly Shaped Clusters and Early Warning System. 'Development of Remote Sensing Methods for Crop Bioterrorism.'  Prospectus 9.

0.10  Patil, G. P. (2002).  Multiscale advanced raster map analysis system:  Development of watershed classification systems for diagnosis of biological impairment in watersheds: Classifying and prioritizing watersheds for protection and restoration.  Prospectus 10.

0.11  Multiscale advanced raster map analysis system:  Network-based analysis of biological integrity in freshwater streams.  Prospectus 11.

0.12  Patil, G. P., Myers, W. L., Taillie, C., and Wardrop, D. (2002).  Hotspot  detection and early warning for synoptic and network-based syndromic surveillance.  Prospectus 12

0.13  Patil, G. P. (2002).  Image processing sensors for autonomous vehicles, robotics and remote sensing: neurovisual fusion architecture for autonomous object detection.  Prospectus 13.

0.14  Patil, G. P. (2002).  GEOINFORMATIC SURVEILLANCE DECISION SUPPORT SYSTEM: Geographic and Network Surveillance for Arbitrarily Shaped Hotspots Next Generation of Geographic Hotspot Detection, Prioritization, and Early Warning with Emerging Hotspots.  Prospectus 14.

0.15  Prospectus 15:  Case Studies and Biographical Sketches.

0.16  Patil, G. P. (2000).  Classified raster map analysis for sustainable environment and development in the 21st Century: A perspective.  (Based on the invited plenary lecture at the Workshop on Statistical Science and Environmental Policy sponsored by the International Statistical Institute, the Bernoulli Society and the Indian Statistical Institute, Calcutta, India, January 2000).  CSEES Technical Report 2000-0801.

0.17  Patil, G. P.  (2000).  Multiscale advanced raster map analysis for sustainable environment and development using remote sensing data.   CSEES Technical Report 2000-0901.   (Invited paper at the Workshop on Tools for Understanding Landscape Patterns in Coastal Areas Induced by Industrialization, Trieste, Italy, September 2000 under the auspices of the United Nations Industrial Develop Organization (UNIDO)).

0.18  Patil, G. P., and Myers, W. L. (1999). Environmental and ecological health assessment of landscapes and watersheds with remote sensing data. Ecosystem Health, 5(4), 221-224, 1999. 

0.19  Patil, G. P. (2003). Geoinformatic surveillance for hotspot detection and prioritization. Innovation with Eplison machines, formal language measures, upper level set scans, partially ordered set prioritizations, decision support systems, and virtual situation room servers. Prospectus 16: Overview.

0.20  Patil, G. P. (2003). Geoinformatic surveillance for hotspot detection and prioritization. Innovation with Eplison machines, formal language measures, upper level set scans, partially ordered set prioritizations, decision support systems, and virtual situation room servers. Prospectus 16.

1) Multiscale Landscape Fragmentation Profiles for Subregion Comparisons

1.1  Johnson, G. D., Myers, W. L., Patil, G. P., and Taillie, C. (2001). Characterizing watershed-delineated landscapes in Pennsylvania using conditional entropy profiles. Landscape Ecology, 16, 597-610, 2001.  (CSEES Technical Report 99-0302).

1.2  Johnson, G. D., Myers, W. L., Patil, G. P., and Taillie, C. (2000). Predictability of surface water pollution loading in Pennsylvania using watershed-based landscape measurements.  Journal of the American Water Resources Association, 37(4), 821-835, 2001. (CSEES Technical Report 99-0303).

1.3 Johnson, G. D., Myers, W. L., Patil, G. P., O'Connell, T. J., and Brooks, R. P. (2002).   Predictability of bird community-based ecological integrity, using landscape measurements. In Managing for Healthy Ecosystems, D. Rapport, W. Lasley, D. Rolston, O. Nielsen, C. Qualset, and A. Damania.  CRC Press/Lewis Press. (To appear).  (CSEES Technical Report 99-0601).

1.4 Johnson, G. D., and Patil, G. P. (1998).  Quantitative multiresolution characterization of landscape patterns for assessing the status of ecosystem health in watershed management areas. Ecosystem Health, 4(3), 177-187.

1.5 Johnson, G. D., Myers, W. L., and Patil, G. P. (1999).  Stochastic generating models for simulating hierarchically structured multi-cover landscapesLandscape Ecology, 14, 413--421.

1.6 Johnson, G. D., Myers, W. L.,  Patil, G. P., and Taillie, C. (1999).  Multiresolution fragmentation profiles for assessing hierarchically structured landscape patterns. Ecological Modeling, 116, 293--301.

1.7  Johnson, G. D., and Patil, G. P. (2001).   Landscape Pattern Analysis for Assessing Ecosystem Condition.  Kluwer Academic Publishers.  pp. 200 (Under preparation).

2) Modeling and Simulation of Multicategorical Raster Maps Using Hierarchical Markov Transition Matrices

2.1 Johnson, G. D., Myers, W. L., Patil, G. P., and Taillie, C. (2001). Fragmentation profiles for real and simulated landscapes. Environmental and Ecological Statistics, 8(1), 5--20. (CSEES Technical Report 99-0102).

2.2  Patil, G. P., and Taillie, C. (1999). 

2.3  Patil, G. P., and Taillie, C. (2000).  A multiscale hierarchical Markov Transition Matrix Model for thematic raster maps.  Environmental and Ecological Statistics, 8(1), 71--84. 

2.4  Patil, G. P., and Taillie (2000).  A computer program for simulating thematic raster maps with the HMTM model.   Technical Report 2000-0604, Center for Statistical Ecology and Environmental Statistics, Department of Statistics, Penn State University, University Park, PA.

2.5 Patil, G. P., and Taillied (2000).  Multiscale frequency table analysis of landscape fragmentation in thematic raster maps. Technical Report 2000-0701, Center for Statistical Ecology and Environmental Statistics, Department of Statistics, Penn State University, University Park, PA.

2.6   Patil, G. P., and Taillie, C. (2000). Properties of binary raster maps generated from the HMTM model. Technical Report 2000-0702, Center for Statistical Ecology and Environmental Statistics, Department of Statistics, Penn State University, University Park, PA. (In preparation).

2.7  Patil, G. P., and Taillie, C. (2000).  Testing for self-similarity of thematic raster maps using the HMTM model.  Technical Report 2000-0703, Center for Statistical Ecology and Environmental Statistics, Department of Statistics, Penn State University, University Park, PA.   (In preparation)

2.8  Patil, G. P., and Taillie, C. (2001).   Modeling Analysis and Simulation of Multicategorical Raster Maps.   Kluwer Academic Publishers.  pp. 200 (Under preparation).

 3)   Understanding Surfaces:   Echelon Analysis of Spatial Structure for Quantitative Geospatial Data

3.1  Myers, W. L., Patil, G. P., and Taillie, C. (1999). Conceptualizing pattern analysis of spectral change relative to ecosystem status. Ecosystem Health, 5(4), 285-293, 1999. 

 3.2 Johnson, G. D., Myers, W. L., Patil, G. P., and Walrath, D. (1998).   Multiscale analysis of the spatial distribution of breeding bird species richness using the echelon approach.  In Assessment of Biodiversity for Improved Forest Planning, P. Bachmann, M. Kohl, and R. Paivinen, eds.  Kluwer Academic Publishers.  pp.  135-150.

 3.3 Myers, W. L., Patil, G. P., and Joly, K. (1997).  Echelon approach to areas of concern in synoptic regional monitoring.  Environmental and Ecological Statistics, 4(2), 131-152.

 3.4   Kurihara, K., Myers, W. L., Patil, G. P. (2000). Relationship of population and land cover pattern based on remote sensing data using echelon analysis. Community Ecology (to appear). (CSEES Technical Report 99-1103)

3.5  Myers, W. L., and Patil, G. P. (2001).   Understanding Surfaces: Echelon Analysis of Spatial Structure for Quantitative Geospatial Data.  Kluwer Academic Publishers.  pp. 200 (Under preparation).

3.6  Myers, W. L., and Patil, G. P. (2002).  Echelon analysis.  In Encyclopedia of Environmetrics, Volume 2.  A. El-Shaarawi and W. W. Piegorsch, eds.  John Wiley & Sons, UK.  pp. 583--586.  (CSEES TR 2001-0205)

4)  Change Detection and Accuracy Assessment Using Error Matrix and Nested Area Sampling Frames

4.1 Patil, G. P., Johnson, G. D., Taillie, C., and Myers, W. L. (2000).  Multiscale statistical approach to critical-area analysis and modeling of watersheds and landscapes.    In Statistics for the 21st Century: Methodologies for Applications of the Future, C. R. Rao and G. J. Szekely, eds.   Marcel Dekker, Inc., New York.  pp. 293--310.  (CSEES Technical Report 99-0502.)

4.2  Patil, G. P., and Taillie, C. (2000).  Modeling and interpreting the accuracy assessment error matrix for a doubly classified map.  Technical Report 2000-0502, Center for Statistical Ecology and Environmental Statistics, Department of Statistics, Penn State University, University Park, PA.

4.2  Patil, G. P., and Taillie, C. (2000).   Analytic solution of the regularized latent truth model for binary maps. Technical Report 2000-0601, Center for Statistical Ecology and Environmental Statistics, Department of Statistics, Penn State University, University Park, PA.

4.3  Patil, G. P., Ray, S., and Taillie, C. (2000).  Performance of adaptive sampling design with nested area sampling frame for binary maps. Technical Report 2000-0720, Center for Statistical Ecology and  Environmental Statistics, Department of Statistics, Penn State University, University Park, PA.  (In preparation).

5) Pattern-Based Compression of Multiband Image Data for Landscape Analysis

5.1  Filipponi, D., Patil, G. P., and Taillie, C. (1998).  Use of indicator kriging to improve spatial coherence of thematic raster maps. Technical Report 98-0103, Center for Statistical Ecology and Environmental Statistics, Department of Statistics, Penn State University, University Park, PA.

5.2  Patil, G. P. and Myers, W. L. (1999). Statistical approaches to multiscale assessment of landscapes and watersheds.

 5.3  Patil, G. P., Myers, W. L., Luo, Z., Johnson G. D., and Taillie, C. (2000).  Multiscale assessment of landscapes and watersheds with synoptic multivariate spatial data in environmental and ecological statistics.  Mathematical and Computer Modeling on Stochastic Models in Mathematical Biology, 32, 257--272.

5.4  Myers, W. L., Patil, G. P., and Taillie, C. (1999).   Adapting quantitative multivariate geographic information system data for purposes of sample design: the phase approach.  In Multivariate Analysis, Design of Experiments and Survey Sampling, Subir Ghosh, ed., Marcel Dekker, Inc., New York

5.5  Myers, W. L., and Patil, G. P. (2001).   Pattern-based Compression of Multiband Image Data for Landscape Analysis.   Kluwer Academc Publishers.  pp. 200.  (Under prepration).

See the following pages for additional references:

Spatial Statistics

Survey Design and Sampling

Statistical Landscape Ecology

Geospatial Multiscale Ecological Assessment